from langchain_core.messages import HumanMessage, SystemMessage, BaseMessage
from langchain_community.chat_models import ChatPerplexity
from langchain_openai import ChatOpenAI

from .prompts import general_model_prompt, opportunity_search_prompt


def invoke_general_model(user_question: str) -> BaseMessage:
    """Function to invoke the general model, to answer general questions related to sales."""
    model = ChatOpenAI(model="gpt-4o-mini")
    system_message = SystemMessage(content=general_model_prompt)
    human_message = HumanMessage(content=user_question)
    response = model.invoke([system_message, human_message])
    return response


def invoke_customer_search(customer_name: str) -> BaseMessage:
    """Function to invoke a Perplexity search on the customer name."""
    model = ChatPerplexity()
    message = HumanMessage(content=opportunity_search_prompt.format(customer_name))
    response = model.invoke([message])
    return response


if __name__ == "__main__":
    from dotenv import load_dotenv

    load_dotenv()

    def test_invoke_general_model():
        # Test that the general model can answer general questions related to sales processes.
        response = invoke_general_model("What is MEDDPICC?")
        assert "MEDDPIC" in response.content
        assert len(response.content) > 10

        # Test that the general model can politely decline to answer questions not related to sales processes.
        response = invoke_general_model("What is the weather like today?")
        assert "weather" not in response.content
        assert "I'm only here to assist you with sales processes and closing deals." in response.content

    def test_invoke_customer_search():
        # Test that the customer search model can find information about a specific company.
        response = invoke_customer_search("Datadog")
        assert "Datadog" in response.content
        assert len(response.content) > 10

    test_invoke_general_model()
    test_invoke_customer_search()